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Article: Approximations of the power functions for Wald, likelihood ratio, and score tests and their applications to linear and logistic regressions.

Demidenko, Eugene

Model assisted statistics and applications : an international journal

2020 Volume 15, Issue 4, Page(s) 335–349

Abstract: Traditionally, asymptotic tests are studied and applied under local alternative (Aivazian, et al., 1985). There exists a widespread opinion that the Wald, likelihood ratio, and score tests are asymptotically equivalent. We dispel this myth by showing ... ...

Abstract	Traditionally, asymptotic tests are studied and applied under local alternative (Aivazian, et al., 1985). There exists a widespread opinion that the Wald, likelihood ratio, and score tests are asymptotically equivalent. We dispel this myth by showing that These tests have different statistical power in the presence of nuisance parameters. The local properties of the tests are described in terms of the first and second derivative evaluated at the null hypothesis. The comparison of the tests are illustrated with two popular regression models: linear regression with random predictor and logistic regression with binary covariate. We study the aberrant behavior of the tests when the distance between the null and alternative does not vanish with the sample size. We demonstrate that these tests have different asymptotic power. In particular, the score test is generally asymptotically biased but slightly superior for linear regression in a close neighborhood of the null. The power approximations are confirmed through simulations.
Language	English
Publishing date	2020-12-25
Publishing country	Netherlands
Document type	Journal Article
ISSN	1574-1699
ISSN	1574-1699
DOI	10.3233/mas-200505
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Article: The next-generation K-means algorithm.

Demidenko, Eugene

Statistical analysis and data mining

2018 Volume 11, Issue 4, Page(s) 153–166

Abstract: Typically, when referring to a model-based classification, the mixture distribution approach is understood. In contrast, we revive the hard-classification model-based approach developed by Banfield and Raftery (1993) for which K-means is equivalent to ... ...

Abstract	Typically, when referring to a model-based classification, the mixture distribution approach is understood. In contrast, we revive the hard-classification model-based approach developed by Banfield and Raftery (1993) for which K-means is equivalent to the maximum likelihood (ML) estimation. The next-generation K-means algorithm does not end after the classification is achieved, but moves forward to answer the following fundamental questions: Are there clusters, how many clusters are there, what are the statistical properties of the estimated means and index sets, what is the distribution of the coefficients in the clusterwise regression, and how to classify multilevel data? The statistical model-based approach for the K-means algorithm is the key, because it allows statistical simulations and studying the properties of classification following the track of the classical statistics. This paper illustrates the application of the ML classification to testing the no-clusters hypothesis, to studying various methods for selection of the number of clusters using simulations, robust clustering using Laplace distribution, studying properties of the coefficients in clusterwise regression, and finally to multilevel data by marrying the variance components model with K-means.
Language	English
Publishing date	2018-05-11
Publishing country	United States
Document type	Journal Article
ZDB-ID	2416076-3
ISSN	1932-1872 ; 1932-1864
ISSN (online)	1932-1872
ISSN	1932-1864
DOI	10.1002/sam.11379
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Article: Optimal Adaptive Designs with Inverse Ordinary Differential Equations.

Demidenko, Eugene

International statistical review = Revue internationale de statistique

2017 Volume 86, Issue 2, Page(s) 169–188

Abstract: Many industrial and engineering applications are built on the basis of differential equations. In some cases, parameters of these equations are not known and are estimated from measurements leading to an inverse problem. Unlike many other papers, we ... ...

Abstract	Many industrial and engineering applications are built on the basis of differential equations. In some cases, parameters of these equations are not known and are estimated from measurements leading to an inverse problem. Unlike many other papers, we suggest to construct new designs in the adaptive fashion 'on the go' using the A-optimality criterion. This approach is demonstrated on determination of optimal locations of measurements and temperature sensors in several engineering applications: (1) determination of the optimal location to measure the height of a hanging wire in order to estimate the sagging parameter with minimum variance (toy example), (2) adaptive determination of optimal locations of temperature sensors in a one-dimensional inverse heat transfer problem and (3) adaptive design in the framework of a one-dimensional diffusion problem when the solution is found numerically using the finite difference approach. In all these problems, statistical criteria for parameter identification and optimal design of experiments are applied. Statistical simulations confirm that estimates derived from the adaptive optimal design converge to the true parameter values with minimum sum of variances when the number of measurements increases. We deliberately chose technically uncomplicated industrial problems to transparently introduce principal ideas of statistical adaptive design.
Language	English
Publishing date	2017-09-08
Publishing country	Netherlands
Document type	Journal Article
ZDB-ID	2045049-7
ISSN	1751-5823 ; 0306-7734
ISSN (online)	1751-5823
ISSN	0306-7734
DOI	10.1111/insr.12233
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Article: Exact and Approximate Statistical Inference for Nonlinear Regression and the Estimating Equation Approach.

Demidenko, Eugene

Scandinavian journal of statistics, theory and applications

2017 Volume 44, Issue 3, Page(s) 636–665

Abstract: The exact density distribution of the nonlinear least squares estimator in the one-parameter regression model is derived in closed form and expressed through the cumulative distribution function of the standard normal variable. Several proposals to ... ...

Abstract	The exact density distribution of the nonlinear least squares estimator in the one-parameter regression model is derived in closed form and expressed through the cumulative distribution function of the standard normal variable. Several proposals to generalize this result are discussed. The exact density is extended to the estimating equation (EE) approach and the nonlinear regression with an arbitrary number of linear parameters and one intrinsically nonlinear parameter. For a very special nonlinear regression model, the derived density coincides with the distribution of the ratio of two normally distributed random variables previously obtained by Fieller (1932), unlike other approximations previously suggested by other authors. Approximations to the density of the EE estimators are discussed in the multivariate case. Numerical complications associated with the nonlinear least squares are illustrated, such as nonexistence and/or multiple solutions, as major factors contributing to poor density approximation. The nonlinear Markov-Gauss theorem is formulated based on the near exact EE density approximation.
Language	English
Publishing date	2017-03-29
Publishing country	England
Document type	Journal Article
ZDB-ID	1466951-1
ISSN	1467-9469 ; 0303-6898
ISSN (online)	1467-9469
ISSN	0303-6898
DOI	10.1111/sjos.12269
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Article: The

Demidenko, Eugene

The American statistician

2016 Volume 70, Issue 1, Page(s) 33–38

Abstract: There is growing frustration with the concept of ... ...

Abstract	There is growing frustration with the concept of the
Language	English
Publishing date	2016-03-31
Publishing country	England
Document type	Journal Article
ZDB-ID	2064982-4
ISSN	1537-2731 ; 0003-1305
ISSN (online)	1537-2731
ISSN	0003-1305
DOI	10.1080/00031305.2015.1069760
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Article: Microarray enriched gene rank.

Demidenko, Eugene

BioData mining

2015 Volume 8, Issue 1, Page(s) 2

Abstract: Background: We develop a new concept that reflects how genes are connected based on microarray data using the coefficient of determination (the squared Pearson correlation coefficient). Our gene rank combines a priori knowledge about gene connectivity, ... ...

Abstract	Background: We develop a new concept that reflects how genes are connected based on microarray data using the coefficient of determination (the squared Pearson correlation coefficient). Our gene rank combines a priori knowledge about gene connectivity, say, from the Gene Ontology (GO) database, and the microarray expression data at hand, called the microarray enriched gene rank, or simply gene rank (GR). GR, similarly to Google PageRank, is defined in a recursive fashion and is computed as the left maximum eigenvector of a stochastic matrix derived from microarray expression data. An efficient algorithm is devised that allows computation of GR for 50 thousand genes with 500 samples within minutes on a personal computer using the public domain statistical package R. Results: Computation of GR is illustrated with several microarray data sets. In particular, we apply GR (1) to answer whether bad genes are more connected than good genes in relation with cancer patient survival, (2) to associate gene connectivity with cluster/subtypes in ovarian cancer tumors, and to determine whether gene connectivity changes (3) from organ to organ within the same organism and (4) between organisms. Conclusions: We have shown by examples that findings based on GR confirm biological expectations. GR may be used for hypothesis generation on gene pathways. It may be used for a homogeneous sample or for comparison of gene connectivity among cases and controls, or in longitudinal setting.
Language	English
Publishing date	2015-01-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2438773-3
ISSN	1756-0381
ISSN	1756-0381
DOI	10.1186/s13040-014-0033-1
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Article ; Online: Estimation of pO

Demidenko, Eugene / Kmiec, Maciej M / Kuppusamy, Periannan

Journal of magnetic resonance (San Diego, Calif. : 1997)

2021 Volume 328, Page(s) 106992

Abstract: Electron paramagnetic resonance (EPR) oximetry, using oxygen-sensing implant such as OxyChip, is capable of measuring oxygen concentration in vivo - a critical tissue information required for successful medical treatment such as cancer, wound healing and ...

Abstract	Electron paramagnetic resonance (EPR) oximetry, using oxygen-sensing implant such as OxyChip, is capable of measuring oxygen concentration in vivo - a critical tissue information required for successful medical treatment such as cancer, wound healing and diabetes. Typically, EPR oximetry produces one value of the oxygen concentration, expressed as pO
MeSH term(s)	Bayes Theorem ; Electron Spin Resonance Spectroscopy ; Humans ; Neoplasms/diagnostic imaging ; Oximetry ; Oxygen
Chemical Substances	Oxygen (S88TT14065)
Language	English
Publishing date	2021-04-28
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ZDB-ID	1469665-4
ISSN	1096-0856 ; 1557-8968 ; 1090-7807 ; 0022-2364
ISSN (online)	1096-0856 ; 1557-8968
ISSN	1090-7807 ; 0022-2364
DOI	10.1016/j.jmr.2021.106992
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Article: Does ROSE matter? Evaluation of final diagnostic, PD-L1 immunohistochemistry, and molecular testing yields of CT-guided lung biopsies performed before and after the onset of the COVID-19 pandemic.

Jennings, Emma B / Percarpio, Robert B / Tafe, Laura J / Demidenko, Eugene / Levy, Joshua / Gutmann, Edward J / Marotti, Jonathan D

Journal of the American Society of Cytopathology

2024

Abstract: Introduction: The onset of the COVID-19 pandemic, with urgent implementation of safety protocols limiting the number of on-site personnel, essentially terminated the use of rapid on-site evaluation (ROSE) for computed tomography (CT)--guided lung ... ...

Abstract	Introduction: The onset of the COVID-19 pandemic, with urgent implementation of safety protocols limiting the number of on-site personnel, essentially terminated the use of rapid on-site evaluation (ROSE) for computed tomography (CT)--guided lung biopsies at our institution. The diminished use of ROSE during the pandemic prompted us to reevaluate the potential value of ROSE for CT-guided lung biopsies. Materials and methods: We retrospectively identified all CT-guided lung biopsies from 2017 to 2022. Associations between the use of ROSE, adequate diagnostic and ancillary testing (programmed death-ligand 1 immunohistochemistry and next-generation sequencing) outcomes, and other factors such as the number of passes performed and lesion size, were evaluated. Results: Nine hundred twelve CT-guided lung biopsies were performed from 2017 to 2022; 171 (19%) utilized ROSE. The use of ROSE had been steadily decreasing prior to the pandemic but was essentially eliminated with the onset of the pandemic. By univariable analysis, the employment of ROSE was more likely to be associated with an adequate final diagnosis (odds ratio = 2.14, 95% confidence interval: [1.24-3.70], P = 0.006) and successful molecular testing (odds ratio = 2.16, 95% confidence interval: [1.11-4.21], P = 0.024). However, those associations were not present in multivariable analyses that incorporated the number of passes performed or lesion size. There were no differences in diagnostic adequacy or ancillary testing yields when comparing the periods 2017-2019 and 2020-2022, despite declining use of ROSE. Conclusions: If ROSE is not requested for CT-guided lung biopsies, proceduralists should err on the side of performing more, rather than fewer, passes, particularly for smaller lesions.
Language	English
Publishing date	2024-03-29
Publishing country	United States
Document type	Journal Article
ISSN	2213-2945
ISSN	2213-2945
DOI	10.1016/j.jasc.2024.03.004
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Article ; Online: In utero

Butler, Erin E / Karagas, Margaret R / Demidenko, Eugene / Bellinger, David C / Korrick, Susan A

Frontiers in epidemiology

2023 Volume 3, Page(s) 1139337

Abstract: Introduction: High-level prenatal and childhood arsenic (As) exposure characteristic of several regions in Asia (e.g., Bangladesh), may impact motor function. However, the relationship between lower-level arsenic exposure (characteristic of other ... ...

Abstract	Introduction: High-level prenatal and childhood arsenic (As) exposure characteristic of several regions in Asia (e.g., Bangladesh), may impact motor function. However, the relationship between lower-level arsenic exposure (characteristic of other regions) and motor development is largely unstudied, despite the potential for deficient motor skills in childhood to have adverse long-term consequences. Thus, we sought to investigate the association between prenatal As exposure and motor function among 395 children in the New Hampshire Birth Cohort Study, a rural cohort from northern New England. Methods: Prenatal exposure was estimated by measuring maternal urine speciated As at 24-28 weeks of gestation using high-performance liquid chromatography (HPLC) inductively coupled plasma mass spectrometry (ICP-MS) and summing inorganic As, monomethylarsonic acid, and dimethylarsinic acid to obtain total urinary As (tAs). Motor function was assessed with the Bruininks-Oseretsky Test of Motor Proficiency, 2nd Edition (BOT-2) at a mean (SD) age of 5.5 (0.4) years. Results: Children who completed this exam were largely reported as white race (97%), born to married mothers (86%) with a college degree or higher (67%). The median (IQR) gestational urine tAs concentration was 4.0 (5.0) µg/L. Mean (SD) BOT-2 scores were 48.6 (8.4) for overall motor proficiency and 48.2 (9.6) for fine manual control [standard score = 50 (10)], and were 16.3 (5.1) for fine motor integration and 12.5 (4.1) for fine motor precision [standard score = 15 (5)]. We found evidence of a non-linear dose response relationship and used a change-point model to assess the association of tAs with overall motor proficiency and indices of fine motor integration, fine motor precision, and their composite, fine manual control, adjusted for age and sex. In models adjusted for potential confounders, each doubling of urine tAs decreased overall motor proficiency by -3.3 points (95% CI: -6.1, -0.4) for tAs concentrations greater than the change point of 9.5 µg/L and decreased fine motor integration by -4.3 points (95% CI: -8.0, -0.6) for tAs concentrations greater than the change point of 17.0 µg/L. Discussion: In summary, we found that levels of prenatal As exposure above an empirically-derived threshold (i.e., the change point) were associated with decrements in childhood motor development in a US population.
Language	English
Publishing date	2023-05-09
Publishing country	Switzerland
Document type	Journal Article
ISSN	2674-1199
ISSN (online)	2674-1199
DOI	10.3389/fepid.2023.1139337
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Article ; Online: Statistical determination of synergy based on Bliss definition of drugs independence.

Demidenko, Eugene / Miller, Todd W

PloS one

2019 Volume 14, Issue 11, Page(s) e0224137

Abstract: Although synergy is a pillar of modern pharmacology, toxicology, and medicine, there is no consensus on its definition despite its nearly one hundred-year history. Moreover, methods for statistical determination of synergy that account for variation of ... ...

Abstract	Although synergy is a pillar of modern pharmacology, toxicology, and medicine, there is no consensus on its definition despite its nearly one hundred-year history. Moreover, methods for statistical determination of synergy that account for variation of response to treatment are underdeveloped and if exist are reduced to the traditional t-test, but do not comply with the normal distribution assumption. We offer statistical models for estimation of synergy using an established definition of Bliss drugs' independence. Although Bliss definition is well-known, it remains a theoretical concept and has never been applied for statistical determination of synergy with various forms of treatment outcome. We rigorously and consistently extend the Bliss definition to detect statistically significant synergy under various designs: (1) in vitro, when the outcome of a cell culture experiment with replicates is the proportion of surviving cells for a single dose or multiple doses, (2) dose-response methodology, (3) in vivo studies in organisms, when the outcome is a longitudinal measurement such as tumor volume, and (4) clinical studies, when the outcome of treatment is measured by survival. For each design, we developed a specific statistical model and demonstrated how to test for independence, synergy, and antagonism, and compute the associated p-value.
MeSH term(s)	Animals ; Antineoplastic Agents/pharmacology ; Antineoplastic Agents/therapeutic use ; Cell Culture Techniques ; Cell Line, Tumor ; Cell Survival/drug effects ; Clinical Trials as Topic ; Disease Models, Animal ; Dose-Response Relationship, Drug ; Drug Antagonism ; Drug Evaluation, Preclinical ; Drug Synergism ; Humans ; Intention to Treat Analysis ; Kaplan-Meier Estimate ; Mice ; Models, Biological ; Neoplasms/drug therapy ; Neoplasms/mortality ; Treatment Outcome
Chemical Substances	Antineoplastic Agents
Language	English
Publishing date	2019-11-25
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural
ISSN	1932-6203
ISSN (online)	1932-6203
DOI	10.1371/journal.pone.0224137
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